Conventionally, the proportional (P), integral (I), and differential (D) control algorithm forming the basis of this type of process control device was a so-called PID control algorithm of one degree of freedom, in which only one of the various control constants (proportional gain, integration time, or derivation time) could be set. Thus, the response characteristic produced by this process control device is set by the condition of adjustment of the various control constants, and, in ordinary process control, when the control object is subjected to an external disturbance, the various control constants are adjusted to suppress the effect of the disturbance rapidly.
However, when the control constants are set in the condition for optimal external disturbance suppression, if the target value is altered, the control amount will overshoot the change in the target value. Also, if the control amount follows the variation of the target amount in an optimal manner, i.e., the control constants are set in an optimum target value tracking characteristic condition, the suppression characteristic with respect to external disturbance is extremely gradual, with the result that the response takes a long time.
Recent attention has been given to this situation. For example, U.S. Pat. No. 4,755,924 of the present applicants describes a two degree of freedom PID control algorithm wherein the control constants can be respectively independently adjusted to the optimum characteristic state in respect of both target value tracking and suppression of external disturbance. By applying this to the entire control system of a plant, the control characteristics can be greatly improved. The most basic element of the algorithm is a target value filter. FIG. 1 is a block diagram showing a conventional process control device having two degrees of freedom of only proportional (P) operation.
The conventional process control device of FIG. 1 includes a difference computing part 10, a main control part 11 of the differential precursor type, a process system 12 as the control object, and compensation control part 13. Difference computing part 10 computes the difference .epsilon. (=SV'-PV) between the correction target value SV' obtained through compensation control part 1 of that target value SV, and the control amount PV that is fed back from control object 13. The main control part 11 performs proportional, integral, and differential computations on this difference .epsilon. based on control constants (proportional gain KP, integration time T.sub.I, and derivation time T.sub.D) adjusted to a characteristic condition such as to optimally suppress fluctuation produced by external disturbance D of control amount PV, and computes adjustment output MV such that control amount PV coincides with target value SV, and outputs this to control object 12. Specifically, main control part 11 consists of proportional +integral computing part 21 (1+(1/T.sub.I .multidot.S)); subtracting part 22; incomplete derivation computing part 23 (T.sub.D .multidot.S)/(1+.eta..multidot.T.sub.D .multidot.S); and proportional gain part 24 (Kp). The difference .epsilon. between control amount PV and target value SV' is fed to proportional +integral computing part 21, and the result of the proportional+integral computation is input to subtracting part 22. Also, control amount PV is fed to incomplete derivation computing part 23, and the result of the incomplete derivation computation is input to subtracting part 22. The result of subtracting these is input to proportional gain part 24, where it is multiplied by proportional gain Kp, and output to control object 12 as the computed adjustment output MV. Control object 12 executes an appropriate control operation with this computed adjustment output MV as its operating amount.
When an external disturbance D is applied and produces a disturbance in control, a fluctuation of control amount PV is detected. Additionally, compensation computing part 13 consists of advance/delay element 1+.alpha..multidot.T.sub.I .multidot.S)/(1+T.sub.I .multidot.S). This aims at giving two degrees of freedom only to proportional (P) operation by effectively revising the proportional gain of main control part 11 to a characteristic condition in which it optimally tracks the variation in target value SV and outputs the revised target value SV'.
In FIG. 1, the transfer function CD(S) of the control algorithm with respect to the change in the external disturbance is: EQU C.sub.D (S)=MV/PV=Kp[(1+(1/T.sub.I .multidot.S)+ EQU (T.sub.D .multidot.S)/(1+.eta..multidot.T.sub.D .multidot.S)](1)
and the transfer function CS(S) of the control algorithm with respect to the variation of the target value is: EQU C.sub.S (S)=MV/SV=((1+.alpha..multidot.T.sub.I .multidot.S)/(1+T.sub.I .multidot.S)).times.Kp (1+1/(T.sub.I .multidot.S))=Kp (1+1)/(T.sub.I .multidot.S) (2)
where K.sub.p, T.sub.I, and T.sub.D are the control constants of the transfer function, respectively indicating the proportional gain, integration time, and derivation time. S is a complex variable (Laplace operator), and .eta. is a constant of about 0.1 to 0.3. The variable .alpha. is the proportional gain revision coefficient for revising the optimum proportional gain K.sub.p for external disturbance suppression to optimal proportional gain K.sub.p * (=.alpha..multidot.K.sub.p) for target value tracking.
Consequently, from equation (1) and equation (2) above, if this proportional gain revision coefficient .alpha. is altered by inserting a compensation control part 13 consisting of advance/delay element (1+.alpha..multidot.T.sub.I .multidot.S)/(1+T.sub.I .multidot.S) on the input line of target value SV as shown in FIG. 1, with the proportional gain of the control algorithm for external disturbance variation as shown in equation (1) still left at K.sub.p, the proportional gain of the control algorithm for a change of target value as shown in equation (2) becomes .alpha..multidot.K.sub.p. Thus, by setting .alpha., the proportional gain K.sub.p can be independently adjusted to an optimum characteristic condition for both target value tracking and external disturbance suppression. That is, there are two degrees of freedom for proportional (P) operation only.
However, in industrial applications, if only proportional (P) operation has two degrees of freedom, optimizing the aforementioned proportional gain revision coefficient .alpha. in each case is impractical when several hundred to several thousand loops are in question, because, strictly speaking, there is an appreciable amount of variation of the characteristic of the control object 12, i.e., this characteristic varies somewhat with the gain, time constant and idle time of the control object 12. Consequently, .alpha. is fixed in the neighborhood of the optimum value using the C.H.R. (Chien, Hrones, Reswich) method. However, by fixing this proportional gain revision coefficient .alpha., the benefit of providing two degrees of freedom in the setting of the control constants of the proportional integral, differential control (i.e. the benefit in terms of improved controllability of simultaneously realizing the characteristics of both external disturbance suppression and target value tracking) is halved in the application to an actual plant.
Thus, with a conventional process control device, there is the problem that the benefit of improving the controllability could not be adequately exhibited by simultaneous realization of both the external disturbance suppression characteristic and target value tracking characteristic.